(620k) Sustainable Optimization of Steam Power Plants

This work presents a new methodology for the multi-objective optimization of steam power plants determining simultaneously the configuration and operational conditions. The proposed methodology is based on search strategy through genetic algorithms because the large sets of nonconvex terms present and to avoid get trapped in a very bad local solution. The proposed methodology considers the optimal selection for the type of fuel used, because this affects drastically the economic and the environmental objective functions; also is considered the selection of a solar collector to provide the required energy because this can be a good option to reduce the green house gas emissions; however the economic objective function is drastically impacted when the solar collector is used. The economic objective function considers the minimization of the total annual cost, including the heating costs (fossil, biofuels and solar), the capital costs for the turbine, condenser, pump, reboiler, deareator, and the solar collector, as well as the operational costs associated to the function of these units. On the other hand, the environmental objective function is based in the eco indicator 99 that measures the overall environmental impact considering the life cycle analysis. These two objectives contradict each other, and the constraint method is used to determine the set of optimal solutions that compensate these two objectives. The proposed methodology allows identifying the incentives required to yield economically attractive a solution that reduces significantly the green house gas emissions.